code: def __parse_items(self):
      self.speaker_to_utters = {}
      for i in self.items:
          path_ = i[1]
          speaker_ = i[2]
          if speaker_ in self.speaker_to_utters.keys():
              self.speaker_to_utters[speaker_].append(path_)
          else:
              self.speaker_to_utters[speaker_] = [
                  path_,
              ]
  
      if self.skip_speakers:
          self.speaker_to_utters = {
              k: v
              for (k, v) in self.speaker_to_utters.items()
              if len(v) >= self.num_utter_per_speaker
          }
  
      self.speakers = [k for (k, v) in self.speaker_to_utters.items()]
  
file_path: TTS/TTS/speaker_encoder/dataset.py
imports: import numpy
  import numpy
  import queue
  import torch
  import random
  from torch.utils.data import Dataset
  from tqdm import tqdm
label_desc: Use image node_id 4 for calling the MyDataset obj's underlying member method code with example usage: obj.__parse_items() without return types